1. Field of the Invention
The present invention is directed to a method correlating measured composition data of oil gathered downhole by a logging tool with predicted composition data of the oil, so as to determine whether Asphaltenes are in an equilibrium distribution within the reservoir in terms of a thermodynamic description and without any exterior influences, e.g., without disturbances from dynamic reservoir processes. More particularly, the invention relates to providing a method for determining the equilibrium distribution of Asphaltenes in oil in a column of a reservoir in terms of gravity and solvency power using downhole logging tools, where the oil is characterized as containing dissolved gases in solution which can be released from the solution (oil) at surface conditions, e.g., live oil.
2. Background of the Invention
Over the years, it was believed that there was fluid homogeneity in a hydrocarbon reservoir. However, there is a growing awareness that fluids are often heterogeneous in the reservoir. Reservoir fluids often demonstrate complicated fluid compositions, properties, and phase behaviors in single columns due to the impacts of gravity, thermal gradients, biodegradation, active charging, water washing, leaky seals, and so on. In addition, reservoir compartmentalization leads to discontinuous compositional distributions. Identifying these discontinuities can provide for a significant cost savings in the overall oil exploration and drilling costs if determined early in the process of extracting oil from the reservoir. Therefore, gathering information on these fluid properties downhole can be a difficult process which may require a greater number of fluid samples and related laboratory analysis. Presently, there is not a theoretical formulism or method in the industry that tests or verifies the sensibility of the collected measured data in the reservoir before commencing drilling operations. In particular, there is not a method that compares gas-oil ratio (GOR) and/or composition and color data and/or asphaltene data of the crude oil with models based on first principles of the asphaltene properties to see if the data makes sense or is even accurate.
Some known methods for collecting measured data in a reservoir include Downhole fluid analysis (DFA) measurements that provide for a useful tool to determine the compositional gradients at downhole conditions in real time. However, as pointed out by Mullins et al. (XXX), for large sand bodies in the Gulf of Mexico, for example, fluid compositional gradients may not be obvious from the properties, e.g., CO2, C1, C2, C3-C5 and C6+, and gas-oil ratio (GOR) measured by DFA tools (see Oliver C. Mullins, Soraya S. Betancourt, Myrt E. Cribbs, Jefferson L. Creek, Francois X. Dubost, A. Ballard Andrews, Lalitha Venkataramanan, Asphaltene Gravitational Gradient in a Deepwater Reservoir as Determined by Downhole Fluid Analysis, , SPE 106375, Houston, 2007). According to the composition and GOR data obtained by the DFA tools, the flow connectivity in the reservoir may not be identified. However, the detailed downhole and laboratory analyses of asphaltene contents (the densest component of crude oils) show apparent asphaltene gradients with depth (although resin gradients are not evident). This information provides for a method that can determine flow connectivity in the reservoir by measuring asphaltene contents with depth at downhole conditions, especially when other fluid property and compositional gradients are not observable. However, this method does not determine the distribution of asphaltenes in live oil in a column of a reservoir in terms the thermodynamic drive of solvency power, where the live oil is defined as containing dissolved gases in solution which can be released from the solution (oil) at surface conditions. Moreover, this method is not a first principles model based on equilibrium distribution and is not based on a known liquid phase composition so as to predict a dissolved asphaltene content in the live oil. Also, current DFA tools cannot directly measure asphaltene content other than the coloration of reservoir fluids which is associated with the asphaltene content.
Referring to aspects of compositional gradients, Equations of state (EoS) models have been used to model the compositional gradients due to the gravitational effects in reservoirs. The standard EoS that can be used in the oil business derives from a modified ideal gas law. For example the popular Peng-Robinson equation of state which is ubiquitous in modeling oil is a modified Van Ver Waals equation of state. In these equations the deviation from the ideal gas law is largely accounted for by 1) introducing a finite (not zero) molecular volume and 2) introducing some intermolecular attraction. These parameters are then related to the critical constants of the different chemical components. Standard EoSs are used throughout to model gas-oil ratio and compositional gradients in oil reservoirs of light ends, alkanes and small aromatics. However, this formalism is not designed to model heavy ends such as asphaltenes. More generally, the treatment of heavy ends is more associated with a constitutive equation which can be used to fit the distribution of asphaltenes based on parameters which may not be explicable from first principles. Nevertheless, to date the industry has handled treatment of asphaltenes in this manner primarily because there had been no agreement about the chemical nature of asphaltenes. If this chemistry is unknown, then a first principles approach is precluded.
Recently, several fundamental chemical properties of asphaltenes have been established. Their molecular weight is now known. (A decade ago, there were orders of magnitude debate about this). In addition, the asphaltene molecular architecture is now largely understood. Finally, the existence of asphaltene nanoaggregates of very small size has now been established in model solvents and in crude oils. Moreover, asphaltenes are much simpler than previously thought making treatment of asphaltenes from first principles much more tractable.
However, there are no known industries or known prior art addressing compositional gradients of asphaltenes (and asphaltene nanoaggregates) within the framework of polymer solution theory (Flory-Huggins theory). Further, there are no known industries or known prior art that are attempting to use the above noted approach in a way designed to handle heavy ends. Moreover, the above mentioned approach is not used with Equation of State (EoS) modeling because EoS modeling is designed to handle light ends while asphaltenes are the heaviest end of crude oil.
Laboratories generally do not treat compositional gradients because typical laboratory fluid columns are less than one foot high so no gradients exist. In the reservoir, it is not uncommon to have a 3,000 feet oil column in a tilted reservoir, thus with such a large column, gradients show up. In addition, because reservoir oils are under high pressure, there can be substantial dissolved gas, unlike a column in a laboratory. It should be noted that dissolved gas increases fluid compressibility giving rise to large density gradients which in turn give rise to large compositional gradients. The reason these gradients in dissolved gas are treated with standard EoS methods is because these methods handle light end distributions. However, since it is very difficult to create large fluid column heights under high pressure in the lab, there was little need (either by industries or inventors) to model compositional gradients of light ends, let alone heavy ends.
U.S. Pat. No. 7,081,615 B2, describes a DFA tool used in acquiring a fluid sample from the formation and incorporated herein by reference. The tool is able to determine compositional data of four or five components and some basic fluid properties, such as live fluid density, viscosity, and coloration. In related U.S. Provisional Patent Application 61/023,135 entitled “Methods of Downhole Fluid Characterization Using Equations of State” (hereafter “'135”) and incorporated herein by reference, the methods of interpreting DFA data are described, which include how to delump C3-C5 (or C2-C5), to characterize C6+ components, to obtain a representative EOS model, and to predict PVT properties. However, U.S. Provisional Patent Application '135 addresses highly non-equilibrium columns where the asphaltene content is controlled by very different mechanisms. In fact, the '135 Provisional Patent Application uses EOS (equation of state) which is based on first principles for the light ends and is not designed to be a first principle approach for the distribution of heavy ends. Also, '135 Provisional Patent Application does not use a polymer solution theory, which is designed to be a first principles approach for components like the asphaltenes and colored components. Moreover, the '135 Provisional Patent Application does not address an equilibrium distribution nor predict the distribution of the asphaltenes in live crude oil in view of known liquid phase compositions at any given depth or location, in terms of the thermodynamic drive of solvency power. Further still, the '135 Provisional Patent Application requires data base of color versus asphaltene content as well as requiring determining the actual asphaltene content. It would be beneficial to develop a new method that does not require having a database of color versus asphaltene content nor having to determine the actual asphaltene content.
Due to the impacts of gravity, chemical forces, molecular and thermal diffusion, natural convection, biodegradation, adsorption, and external fluxes, non-equilibrium hydrocarbon distribution frequently can exists in the reservoir. Determination of compositional and property gradients, and reservoir connectivity, can be of importance to the oil and gas industry. DFA tools are useful and powerful for determining compositional and property gradients with depth at downhole conditions in real time. Where compositional and property gradients with depth in the reservoir are unobservable by means of DFA tools, a method of associating the coloration measured by DFA tools with asphaltene content, and then determining the distribution of asphaltenes and color components solvated in the liquid phase of live oil, in terms of the thermodynamic drive of gravity and solvency may be required.
In the Buckley reference, the Flory-Huggins model is applied to homogeneous mixtures of oils with asphaltenes, in order to predict the onset of flocculation. It does not address the equilibrium behavior of asphaltenes subject to gravity effects in oils with compositional gradients (see Jill Buckley is J. X. Wang and J. S. Buckley, “A Two-Component Solubility Model of the Onset of Asphaltene Flocculation in Crude Oils”, Energy and Fuels 2001, 15, 1004-1012.).
Mullins, and Betancourt consider gradients in asphaltenes due to gravity effects in oil columns (see Oliver C. Mullins, Soraya S. Betancourt, Myrt E. Cribbs, Francois X. Dubost, Jefferson L. Creek, A. Ballard Andrews, and Lalitha Venkataramanan, “The Colloidal Structure of Crude Oil and the Structure of Oil Reservoirs”, Energy & Fuels 2007, 21, 2785-2794) (see Soraya S. Betancourt, Francois X. Dubost, Oliver C. Mullins, Myrt E. Cribbs, Jefferson L. Creek, Syrizc G. Mathews, “Predicting Downhole Fluid Analysis Logs to Investigate Reservoir Connectivity”, International Petroleum Technology Conference, IPTC 11488, Dubai, UAE, Dec. 4-6, 2007.). The columns in these papers do not have large amounts of dissolved gas, so the solubility (and entropy) effects are not addressed.
Fujisawa at el. and Dubost et al. consider an oil column where there is a gradient in both the light ends and the color (see F. Dubost, A. Carnegie, O. C. Mullins, M. O. Keefe, S. Betancourt, J. Y. Zuo, and K. O. Eriksen, “Integration of In-Situ Fluid Measurements for Pressure Gradients Calculations”, SPE 108494, 2007). The one by Fujisawa et al. does not give a model for any of the compositional gradients, including asphaltene gradients (see G. Fujisawa, S. S. Betancourt, O. C. Mullins, T. Torgersen, T. Terabayashi, C. Dong, K. O. Eriksen, “Large Hydrocarbon Compositional Gradient Revealed by In-Situ Optical Spectroscopy”, SPE 89704, SPE ATCE Houston, September 2004.). It only says that if there is a variation in the composition, additional samples should be taken.
The paper by Dubost et al. (noted above) uses an EoS model for the fluid to find a method for properly fitting the pressure data and does not address the asphaltene or color gradient.
Standard references on compositional grading in oil columns, such as Whitson et al., (see Lars Høier, SPE, Statoil and Curtis H. Whitson, “Compositional Grading—Theory and Practice”, NTNU/Pera, SPE 63085, 2000 SPE Annual Technical Conference and Exhibition Dallas, Tex., 1-4 Oct. 2000), Model at al. (see F. Montel and P. L. Gouel, Elf, “Prediction of Compositional Grading in a Reservoir Fluid Column”, SPE 14410, presentation at the Wth Annual Technical Conference and Exhibition of the Society of Petroleum Engineers held in Las Vagaa, Nev. Sep. 22-25, 1995.) and Firoozabadi et al. (see Carlos Lira-Galeana, Abbas Firoozabadi, and John M. Prausnitz, “Computation of Compositional Grading in Hydrocarbon Reservoirs, Application of Continuous Thermodynamics”, Fluid Phase Equilibria, 102 (1994), 143-158.) use equation of state methods.